Damage assessment of the truss system with uncertainty using frequency response function based damage identification method

2015 ◽  
Author(s):  
Jie Zhao ◽  
Hans DeSmidt ◽  
Wei Yao
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Damage Assessment ◽  
Frequency Response Function ◽  
Damage Identification ◽  
Identification Method

Substructure Damage Identification Based on Model Updating of Frequency Response Function

2021 ◽  
pp. 2150171
Author(s):  
Youliang Fang ◽  
Pengrui Su ◽  
Jingyu Shao ◽  
Jiaqi Lou ◽  
Ying Zhang
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Large Scale ◽  
Damage Identification ◽  
Model Updating ◽  
Mass Matrix ◽  
Frame Structure ◽  
Simplified Model ◽  
Identification Method

Model updating of large-scale structures is difficult to carry out when using a frequency response function (FRF) for damage identification, as the solutions for the global system matrices with too many degrees of freedom are required in each iteration. In this paper, a substructure damage identification method is proposed based on the model updating of the acceleration FRF. The original finite element model is divided into several substructures using the improved reduced system (IRS) by the dynamic condensation method, resulting in the simplified substructure model. The final simplified model is composed of the simplified mass matrix and stiffness matrix of the substructure considered. The damage acceleration FRF to be identified is used to iteratively update the simplified model. The locations and extents of the damage elements are obtained by updating the results, which reduces the number of uncertain parameters to be updated and leads to the rapid convergence of the optimization process. In the iteration, L1 norm regularization is introduced to solve the ill-posed problem, which improves the stability of the identification results. A numerical simulation of a six-story steel frame structure under various working conditions was carried out to verify the effectiveness of the proposed method, which was also validated by the experiments. The robustness and performance of the proposed damage identification method based on substructures have been demonstrated.

Study on Benchmark Structure Damage Identification Base on Frequency Response Function and Genetic Algorithm

2010 ◽  
Vol 163-167 ◽  
pp. 2765-2769 ◽  
Author(s):  
Wan Jie Zou ◽  
Zhen Luo ◽  
Guo En Zhou
Keyword(s):  
Genetic Algorithm ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Damage Identification ◽  
Fitness Function ◽  
Floating Point ◽  
Combined Method ◽  
Structure Damage ◽  
Floating Point Number

A combined method for the Benchmark structure damage identification base on the frequency response function(FRF) and genetic algorithm(GA) is presented. The reducing factors of element stiffness are used as the optimization variables, and the cross signature assurance criterion (CSAC) of the test FRF and the analysis FRF is used to constructing the optimization object function and the fitness function of the GA. To avoid the weakness of binary encoding, the floating point number encoding is used in the GA. At last, the Benchmark structure established by IASC-ASCE SHM group is caculated by the proposed method, the results show that even if the serious testing noise is considered, the patterns of damage of the Benchmark structure can be identified well. The effectiveness of the presented method is verified.

Damage identification using structural modes based on substructure virtual distortion method

2016 ◽  
Vol 20 (2) ◽  
pp. 257-271 ◽  
Author(s):  
Qingxia Zhang ◽  
Łukasz Jankowski
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Structural Damage ◽  
Frequency Response Function ◽  
Damage Identification ◽  
Element Model ◽  
Frequency Responses ◽  
Computational Work ◽  
Structural Reanalysis ◽  
Identification Approach

A damage identification approach is presented using substructure virtual distortion method which takes the advantage of the fast structural reanalysis technique of virtual distortion method. The formulas of substructure virtual distortion method are deduced in frequency domain, and then the frequency response function of the damaged structure is constructed quickly via the superposition of the frequency response function of the intact structure and the frequency responses caused by the damage-coupling virtual distortions of the substructures. The structural damage extents are identified using the measured modal parameters. Two steps are adopted to increase the efficiency of optimization: the modals of finite element model are estimated quickly from the fast constructed frequency response function during the optimization and the primary distortions of the substructures are extracted by contribution analysis to further reduce the computational work. A six-story frame numerical model and an experiment of a cantilever beam are carried out, respectively, to verify the efficiency and accuracy of the proposed method.

Structural Damage Identification Based on Strain Frequency Response Functions

2018 ◽  
Vol 18 (12) ◽  
pp. 1850159 ◽  
Author(s):  
Fariba Shadan ◽  
Faramarz Khoshnoudian ◽  
Akbar Esfandiari
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Dynamic Characteristics ◽  
Structural Damage ◽  
Frequency Response Function ◽  
Damage Identification ◽  
Model Updating ◽  
Measurement Data ◽  
Sensitivity Equation ◽  
Strain Frequency

Damage identification using the sensitivity of the dynamic characteristics of the structure of concern has been studied considerably. Among the dynamic characteristics used to locate and quantify structural damages, the frequency response function (FRF) data has the advantage of avoiding modal analysis errors. Additionally, previous studies demonstrated that strains are more sensitive to localized damages compared to displacements. So, in this study, the strain frequency response function (SFRF) data is utilized to identify structural damages using a sensitivity-based model updating approach. A pseudo-linear sensitivity equation which removes the adverse effects of incomplete measurement data is proposed. The approximation used for the sensitivity equation utilizes measured natural frequencies to reconstruct the unmeasured SFRFs. Moreover, new approaches are proposed for selecting the excitation and measurement locations for effective model updating. The efficiency of the proposed method is validated numerically through 2D truss and frame examples using incomplete and noise polluted SFRF data. Results indicate that the method can be used to accurately locate and quantify the severity of damage.

scholarly journals Single Pick Cutting Rock Load Identification Based on Improved Regularization Method

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Lei Dong ◽  
Siyu Zhai ◽  
Bukang Wang ◽  
Liang Dong ◽  
Junyuan Wang ◽  
...  
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Regularization Method ◽  
Frequency Response Function ◽  
Cutting Speed ◽  
Vibration Signal ◽  
Maximum Load ◽  
Load Identification ◽  
Identification Method ◽  
Rock Load

To explore the relationship between the cutting vibration and the cutting load of a single pick, this paper studied a new method for a single pick cutting rock load identification. This paper improved the low accuracy problem of the regularization method in the inverse process of frequency response function in the traditional load identification method by introducing a filter operator. By combining the inverse pseudoexcitation method and the improved regularization method, the identification of the load dependent on the vibration signal was realized. A single pick cutting rock test equipment was built, which could simulate the actual working conditions of pick cutting rock in the underground or tunnel. By changing cutting speed, cutting angle, cutting spacing, and cutting depth of the single pick, the change trends of real cutting load and identification load were obtained. The load identification method proposed in this paper was consistent with the change trend of the real load under the single pick cutting state. Therefore, the method had good recognition accuracy and the maximum load recognition error was 17.35%. Compared with other traditional load identification methods, the identification error was reduced by a maximum of 1.98%. This method can identify the cutting load of single pick and modify the morbidity problem of frequency response function matrix. The method has a better recognition effect on the cutting load of the pick than the traditional recognition methods. The research could benefit the design of the cutting system and the arrangement of the pick on the coal mine or tunneling machinery.

scholarly journals Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 220 ◽  
Author(s):  
Jilin Hou ◽  
Pengfei Wang ◽  
Tianyu Jing ◽  
Łukasz Jankowski
Keyword(s):  
Experimental Study ◽  
Finite Element ◽  
Frequency Response ◽  
Response Function ◽  
Storage Tank ◽  
Frequency Response Function ◽  
Damage Identification ◽  
Fe Model ◽  
Storage Tanks ◽  
Identification Approach

This research proposes a damage identification approach for storage tanks that is based on adding virtual masses. First, the frequency response function of a structure with additional virtual masses is deduced based on the Virtual Distortion Method (VDM). Subsequently, a Finite Element (FE) model of a storage tank is established to verify the proposed method; the relation between the added virtual masses and the sensitivity of the virtual structure is analyzed to determine the optimal mass and the corresponding frequency with the highest sensitivity with respect to potential damages. Thereupon, the damage can be localized and quantified by comparing the damage factors of substructures. Finally, an experimental study is conducted on a storage tank. The results confirm that the proposed method is feasible and practical, and that it can be applied for damage identification of storage tanks.

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